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EPIC SIGNED

Evolving Program Improvement Collaborators

Total Cost €

EC-Contrib. €

Partnership

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EPIC project word cloud

Explore the words cloud of the EPIC project. It provides you a very rough idea of what is the project "EPIC" about.

emergent competing genetic strengths spaces entirely identification evolutionary introduce intelligently improvement improvements underpinned engineering multiplicity multiple platforms previously conflicting grafting keywords epic programming automatically epi human unexposed search complementary domain construct quantitative collaborators software contextual computing optimising versions optimisation sbse host suggest explains grown machine tackles transplantation algorithms justifies constructed code deep tuneable collaborator donor unexploited functional suggestions insights documents

Project "EPIC" data sheet

The following table provides information about the project.

Coordinator	UNIVERSITY COLLEGE LONDON Organization address address: GOWER STREET city: LONDON postcode: WC1E 6BT website: n.a. contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	United Kingdom [UK]
Total cost	2˙159˙035 €
EC max contribution	2˙159˙035 € (100%)
Programme	1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
Code Call	ERC-2016-ADG
Funding Scheme	ERC-ADG
Starting year	2017
Duration (year-month-day)	from 2017-10-01 to 2022-09-30

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	UNIVERSITY COLLEGE LONDON UNIVERSITY COLLEGE LONDON Organization address address: GOWER STREET city: LONDON postcode: WC1E 6BT website: n.a. contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	UK (LONDON)	coordinator	2˙159˙035.00

Map

Project objective

EPIC will automatically construct Evolutionary Program Improvement Collaborators (called Epi-Collaborators) that suggest code changes that improve software according to multiple functional and non-functional objectives. The Epi-Collaborator suggestions will include transplantation of code from a donor system to a host, grafting of entirely new features `grown' (evolved) by the Epi-Collaborator, and identification and optimisation of tuneable `deep' parameters (that were previously unexposed and therefore unexploited).

A key feature of the EPIC approach is that all of these suggestions will be underpinned by automatically-constructed quantitative evidence that justifies, explains and documents improvements. EPIC aims to introduce a new way of developing software, as a collaboration between human and machine, exploiting the complementary strengths of each; the human has domain and contextual insights, while the machine has the ability to intelligently search large search spaces. The EPIC approach directly tackles the emergent challenges of multiplicity: optimising for multiple competing and conflicting objectives and platforms with multiple software versions.

Keywords: Search Based Software Engineering (SBSE), Evolutionary Computing, Software Testing, Genetic Algorithms, Genetic Programming.

Publications

List of publications.
year	authors and title	journal	last update
2018	Marinos Kintis, Mike Papadakis, Yue Jia, Nicos Malevris, Yves Le Traon, Mark Harman Detecting Trivial Mutant Equivalences via Compiler Optimisations published pages: 308-333, ISSN: 0098-5589, DOI: 10.1109/tse.2017.2684805	IEEE Transactions on Software Engineering 44/4	2019-08-05
2018	Justyna Petke, Mark Harman, William B. Langdon, Westley Weimer Specialising Software for Different Downstream Applications Using Genetic Improvement and Code Transplantation published pages: 574-594, ISSN: 0098-5589, DOI: 10.1109/tse.2017.2702606	IEEE Transactions on Software Engineering 44/6	2019-08-05
2018	Yuanyuan Zhang, Mark Harman, Gabriela Ochoa, Guenther Ruhe, Sjaak Brinkkemper An Empirical Study of Meta- and Hyper-Heuristic Search for Multi-Objective Release Planning published pages: 1-32, ISSN: 1049-331X, DOI: 10.1145/3196831	ACM Transactions on Software Engineering and Methodology 27/1	2019-08-05
2018	Justyna Petke, Saemundur O. Haraldsson, Mark Harman, William B. Langdon, David R. White, John R. Woodward Genetic Improvement of Software: A Comprehensive Survey published pages: 415-432, ISSN: 1089-778X, DOI: 10.1109/tevc.2017.2693219	IEEE Transactions on Evolutionary Computation 22/3	2019-08-05
2018	Matheus Paixao, Mark Harman, Yuanyuan Zhang, Yijun Yu An Empirical Study of Cohesion and Coupling: Balancing Optimization and Disruption published pages: 394-414, ISSN: 1089-778X, DOI: 10.1109/tevc.2017.2691281	IEEE Transactions on Evolutionary Computation 22/3	2019-08-05

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The information about "EPIC" are provided by the European Opendata Portal: CORDIS opendata.